Kerja Cloud Engineering - AI Enablement Intern (Jan 2027 intake) di Crédit Agricole CIB - Maukerja

This is a 6-month full-time on-site internship program starting from Jan 2027.

Who we are

Crédit Agricole Corporate and Investment Bank (Crédit Agricole CIB) is the corporate and investment banking arm of Crédit Agricole Group, world’s 10th largest bank by total assets.

Our Singapore center is the 2nd largest IT setup (after Paris Head Office) for Crédit Agricole CIB's worldwide business. We work daily with international branches located in 30 markets by:

• Envisioning and preparing the Bank’s futures information systems
• Partnering and supporting core banking flagships and transverse areas in their large scale development projects
• Providing premium In-house Banking applications

This unique positioning empowers us to bring our core banking business a sustainable competitive advantage on the market.

We seek innovative and agile people sharing our mindset to support ambitious and forthcoming technological challenges.

Role Overview

We are looking for an intern interested in cloud engineering and practical AI applications. This role provides equal exposure to cloud and Kubernetes engineering, alongside AI enablement and support for our AI-assisted development tools rollout.

You will learn to deploy and support cloud-based applications, work with containers and Kubernetes, and help users adopt AI tools effectively and responsibly through guided engineering tasks and user-support activities.

Key Responsibilities

Cloud Engineering and Kubernetes

• Learn and apply cloud fundamentals using major cloud platform(s), including compute, networking, identity, storage, and monitoring.
• Support cloud environment setup, configuration, and troubleshooting under guidance.
• Gain hands-on experience with containers and Kubernetes, including pods, deployments, services, and configuration.
• Assist with application deployments, monitoring, and troubleshooting in development or sandbox environments.
• Contribute to automation scripts, operational documentation, and reusable deployment configurations.
• Follow established security, access-control, and cloud cost-management practices.

AI Engineering and Enablement

• Help configure and use AI tools to connect operational context, tools, and workflows supporting department activities.
• Support enterprise AI tool onboarding, adoption, and common user queries within IT Operations.
• Explore use cases such as incident investigation, log analysis, troubleshooting, runbook execution, and operational documentation.
• Assist with integrating approved knowledge sources, scripts, and tools into AI workflows under guidance.
• Apply prompt design and context management to improve responses and explain relevant AI concepts and limitations to users.
• Build and test small operational automations, validating outputs and retaining human approval for actions that change systems.
• Prepare demonstrations, FAQs, and reusable examples; gather feedback to improve operational usefulness.
• Follow organizational requirements for access control, confidential data, auditability, and responsible AI usage.

Qualifications and Profile

Currently pursuing Master’s or Bachelor’s Degree in Computer Science, Information Technology, Software Engineering, or related fields.

• Foundational programming or scripting ability in Python, JavaScript/TypeScript, or a similar language.
• Basic understanding of cloud computing and generative AI, with an interest in developing practical skills in both.
• Familiarity with Git, an IDE such as VS Code, and basic command-line usage.
• A structured approach to troubleshooting and a willingness to learn through hands-on tasks.
• Ability to explain technical concepts clearly, document solutions, and collaborate with users and engineers.
• Customer service oriented and a strong team player

Good to have:

• Introductory exposure to cloud computing platforms, Docker, or Kubernetes.
• Academic or personal projects involving application deployment, infrastructure automation, or cloud services.
• Experience using AI-assisted development tool.
• Exposure to AI APIs, prompt engineering, chatbots, or automation projects.

Learning Opportunities

• Guided, hands-on experience with cloud infrastructure, containers, and Kubernetes.
• Practical experience supporting an enterprise AI tool rollout and answering AI-related questions.
• Exposure to automation, AI engineering, and responsible technology adoption.
• Opportunities to contribute working prototypes, deployment configurations, and reusable technical documentation.